Proving or Disproving Null Space Containment in F(n) for A and A^2

In summary: In summary, the conversation discusses a homework problem that requires proving or disproving a statement involving null spaces, rank, and dimensions of matrices. The participants also discuss the use of the definition in the proof. One participant provides a solution using the definition and the other gives a suggestion for improving the proof.
  • #1
sarumman
2
1

Homework Statement


given
upload_2018-12-19_23-51-14.png
I am required to proove or disprove:[/B]
lTxizl2.jpg


Homework Equations


rank
dim
null space

The Attempt at a Solution


I tried to base my answer based on the fact that null A and null A^2 is Contained in F (n)
and
dim N(A)+rank(A)=N
same goes for A^2.
 

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  • #2
Why don't you just use the definition?

##x \in Null(A) \implies Ax = 0 ##

If the statement is true, you have to prove that ##A^2 x = 0##. Can you show that?
 
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  • #3
Math_QED said:
Why don't you just use the definition?

##x \in Null(A) \implies Ax = 0 ##

If the statement is true, you have to prove that ##A^2 x = 0##. Can you show that?
thank you! you mean like so:
upload_2018-12-20_0-5-50.png
 

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  • #4
Yes, the idea is certainly correct. The proof exposition can be better though. Here is how I would write it:

We want to prove that ##Null(A) \subseteq Null(A^2)##, so let's take an arbitrary element ##x \in Null(A)##. By definition, this means that ##Ax = 0##. Since ##A^2x = (AA)x = A(Ax) = A0 = 0## (here we used associativity of matrix multiplication/function composition), it follows that ##x \in Null(A^2)##, and we are done.
 
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What is the null space of a matrix?

The null space of a matrix, also known as the kernel, is the set of all vectors that when multiplied by the matrix, result in a vector of zeros. In other words, it is the set of all solutions to the homogeneous equation Ax = 0, where A is the given matrix.

How do you find the null space of a matrix?

To find the null space of a matrix, you can use Gaussian elimination or row reduction to put the matrix in reduced row echelon form. The columns without pivot positions correspond to the free variables, and the null space can be expressed as a linear combination of these variables.

What is the dimension of the null space of a matrix?

The dimension of the null space of a matrix is also known as the nullity, and it is equal to the number of free variables in the reduced row echelon form of the matrix. In other words, it is the number of linearly independent vectors in the null space.

What is the relationship between the null space and the column space of a matrix?

The null space and column space of a matrix are complementary subspaces. This means that the dimension of the null space and the dimension of the column space add up to the total number of columns in the matrix.

What is the significance of the null space in linear algebra?

The null space is significant in linear algebra as it helps us understand the solutions to systems of linear equations. It can also be used to find the basis for the column space of a matrix, which is useful in solving systems of equations and finding solutions to linear transformations.

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